Arousal electrical stimulation system for rehabilitation of disorders of consciousness, and method

Abstract

Provided in the present application are an arousal electrical stimulation system for rehabilitation of disorders of consciousness and a method. The system comprises: a program control module, used for setting a plurality of stimulation point combinations and a plurality of stimulation parameter combinations; an implanted spinal cord stimulation module, used for sequentially outputting stimulation signals according to the plurality of stimulation point combinations and the plurality of stimulation parameter combinations; an acquisition module, used for acquiring electroencephalographic signals and electromyographic signals when the stimulation signals act on a patient suffering from disorders of consciousness; and a processing module, used for processing the electroencephalographic signals and the electromyographic signals to obtain a human body index, and, on the basis of the human body index, determining an optimal stimulation point combination and an optimal stimulation parameter combination from among the plurality of stimulation point combinations and the plurality of stimulation parameter combinations. The present invention uses the cooperation of in-vitro electroencephalographic and electromyographic sampling devices and a spinal cord electric stimulation device implanted into the human body, and performs calculation by means of the processing module, so as to obtain the optimal electric stimulation electrode point combination and the optimal electric stimulation parameter combination, thereby improving the arousal efficiency.

Description

Awakening electrical stimulation system and method for rehabilitation of consciousness disorders Technical Field

[0001] The present application relates to the field of medical equipment, and specifically to a wake-promoting electrical stimulation system and method for rehabilitation of consciousness disorders. Background Art

[0002] Prolonged disorders of consciousness (pDoC) refer to pathological states characterized by loss of consciousness for more than 28 days, resulting from various brain injuries, such as traumatic brain injury, stroke, and hypoxic-ischemic encephalopathy. These states can be categorized as vegetative state (VS), unresponsive wakefulness syndrome (UWS), or minimally conscious state (MCS). pDoC patients suffer from severe neurological damage, accompanied by complex functional impairments and complications, and their recovery is long and challenging. Therefore, rehabilitation is crucial throughout the treatment cycle for pDoC patients, yet it also presents significant challenges.

[0003] Currently, there are a variety of clinical treatments for people with impaired consciousness, including non-invasive sensory stimulation, non-invasive electrical stimulation, implantable spinal cord electrical stimulation, and implantable brain pacemaker stimulation. Effective treatments have been developed for different groups of people with impaired consciousness. In particular, implantable electrical stimulation therapy, which has emerged in recent years, can directly and precisely stimulate the nervous system of patients with impaired consciousness due to its direct contact with the central nervous system.

[0004] However, due to the lack of effective feedback capabilities of the conscious group, it is impossible to understand whether the stimulation points, stimulation methods and stimulation parameters during the medical process are effective for the patients. Therefore, what channels and methods are used to determine the effective stimulation points, stimulation methods and stimulation parameters is particularly important in the entire treatment process. Currently, this means is lacking in clinical practice.

[0005] Summary of the Invention

[0006] In view of this, the present application provides a system for promoting awakening for rehabilitation of impaired consciousness, comprising:

[0007] a programmable control module, configured to set a plurality of stimulation point combinations and a plurality of stimulation parameter combinations, wherein the differences between the different stimulation point combinations include at least one of the number of points, the site of action, and the polarity; the stimulation parameters include at least one of the stimulation amplitude, the stimulation frequency, and the pulse width; and the differences between the different stimulation parameter combinations include a different value of at least one of the parameters;

[0008] An implantable spinal cord stimulation module, configured to sequentially output stimulation signals according to the plurality of stimulation point combinations and the plurality of stimulation parameter combinations;

[0009] an acquisition module, configured to acquire EEG signals and EMG signals when the stimulation signal acts on a patient with impaired consciousness;

[0010] A processing module is used to process the EEG signal and the EMG signal to obtain human body indicators, and determine the optimal stimulation point combination and the optimal stimulation parameter combination from the multiple stimulation point combinations and the multiple stimulation parameter combinations according to the human body indicators.

[0011] The awakening system for rehabilitation of impaired consciousness provided by the present invention forms a closed-loop system by cooperating with an external EEG and EMG sampling device and a spinal cord electrical stimulation device implanted in the human body. By collecting and calculating real-time EEG and EMG information in the closed-loop system, the optimal combination of electrical stimulation electrode points and electrical stimulation parameters are obtained. This system can determine the most effective stimulation points and stimulation parameters for the patient based on objective physical indicators, without the need for subjective feedback from the patient. It is suitable for people with impaired consciousness and improves the efficiency of awakening.

[0012] This application provides a method for determining a wake-promoting electrical stimulation program for rehabilitation of impaired consciousness, comprising:

[0013] In the process of the implantable spinal cord stimulator using preset stimulation parameters and sequentially outputting stimulation signals through a plurality of stimulation point combinations, the human body's electroencephalogram (EEG) signals and myoelectric signals are collected;

[0014] Calculating human body indicators based on the EEG signals and the EMG signals corresponding to each stimulation point combination;

[0015] Determining an optimal stimulation point combination from the plurality of stimulation point combinations according to the human body indicators;

[0016] In the process of the implantable spinal cord stimulator outputting stimulation signals respectively through the optimal stimulation point combination and sequentially using multiple stimulation parameter combinations, collecting brain electrical signals and myoelectric signals of the human body;

[0017] Calculating human body indicators based on the EEG signal and the EMG signal corresponding to each stimulation parameter combination;

[0018] An optimal stimulation parameter combination is determined from the multiple stimulation parameter combinations according to the human body indicators.

[0019] According to the method for determining an electrical stimulation scheme provided in an embodiment of the present application, first, under the condition of fixed stimulation parameters, electrical stimulation signals are output through different stimulation point combinations, the patient's physical indicators are collected, and their response to different points is determined, so that the most effective stimulation points for awakening can be determined; then, the currently determined optimal stimulation point combination is locked, stimulation signals are output using different stimulation parameters, and the patient's physical indicators are collected again to determine their response to different stimulation parameters, so that the most effective stimulation parameters for awakening can be determined. Through a two-stage finite number of polling, the most effective stimulation points and stimulation parameters for the patient can be determined based on objective physical indicators. This scheme does not require subjective feedback from the patient and is suitable for people with impaired consciousness. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the specific implementation methods of the present application or the technical solutions in the prior art, the following is a brief introduction to the drawings required for use in the specific implementation methods or the description of the prior art. Obviously, the drawings described below are some implementation methods of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0021] FIG1 is a schematic structural diagram of a wake-up system provided in an embodiment of the present application;

[0022] FIG2 is a schematic diagram of a front view of the awakening system provided in an embodiment of the present application;

[0023] FIG3 is a side view schematic diagram of the awakening system provided in an embodiment of the present application;

[0024] FIG4 is a schematic diagram of the operation flow of the awakening system provided in an embodiment of the present application;

[0025] FIG5 is a flow chart of a method for determining a wake-promoting electrical stimulation scheme in an embodiment of the present application;

[0026] FIG6 is a flow chart of a second method for determining a wake-promoting electrical stimulation scheme according to an embodiment of the present application;

[0027] FIG7 is a flow chart of a third method for determining a wake-promoting electrical stimulation scheme in an embodiment of the present application;

[0028] FIG8 is a flowchart of a fourth method for determining a wake-up electrical stimulation scheme in an embodiment of the present application. DETAILED DESCRIPTION

[0029] The following will clearly and completely describe the technical solution of this application in conjunction with the accompanying drawings. Obviously, the embodiments described are only part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making any creative efforts are within the scope of protection of this application.

[0030] The technical features involved in the different embodiments of the present application described below can be combined with each other as long as they do not conflict with each other.

[0031] As shown in FIG1 , an embodiment of the present application provides a system for promoting awakening for patients with impaired consciousness, comprising: an acquisition module 1, a processing module 2, a program control module 3, and an implantable spinal cord stimulation module 4, wherein:

[0032] Programmable control module 3, for setting multiple stimulation point combinations and multiple stimulation parameter combinations, wherein different stimulation point combinations differ in at least one of the number of points, site of action, and polarity; stimulation parameters include at least one of stimulation amplitude, stimulation frequency, and pulse width, and different stimulation parameter combinations differ in the value of at least one of the parameters;

[0033] An implantable spinal cord stimulation module 4 is configured to sequentially output stimulation signals according to a plurality of stimulation point combinations and a plurality of stimulation parameter combinations;

[0034] Acquisition module 1, used to collect EEG signals and EMG signals when stimulation signals act on patients with impaired consciousness;

[0035] The processing module 2 is used to process the EEG signal and the EMG signal to obtain human body indicators, and determine the optimal stimulation point combination and the optimal stimulation parameter combination from multiple stimulation point combinations and multiple stimulation parameter combinations according to the human body indicators.

[0036] After receiving the patient's EEG and EMG information, this system analyzes the patient's EEG and EMG information, and adjusts the electrode position, electrical stimulation amplitude, electrical stimulation pulse width, electrical stimulation frequency and other parameters of the implantable spinal cord stimulator by controlling the implantable spinal cord stimulator. The implantable spinal cord stimulator can introduce stimulation pulses directly into the central nervous system through electrodes implanted inside the human body, significantly improving the accuracy and efficiency of electrical stimulation. Through the cooperation of external EEG and EMG sampling equipment and the spinal cord stimulation equipment implanted in the human body, a closed-loop system is formed. Through the real-time EEG and EMG information collection and calculation in the closed-loop system, the optimal combination of electrical stimulation electrode points and electrical stimulation parameters are obtained, thereby improving the efficiency of awakening.

[0037] As shown in FIG3 , in a preferred embodiment, the program control module 3 includes a first signal input unit 31 , a stimulation point parameter setting unit 32 , a stimulation parameter setting unit 33 and a parameter wireless output unit 34 ;

[0038] The first signal input unit 31 is used to receive a number of stimulation points and a number of stimulation parameters;

[0039] A stimulation point parameter setting unit 32 is used to set a plurality of stimulation point combinations according to a plurality of stimulation points;

[0040] a stimulation parameter setting unit 33, configured to set a plurality of stimulation parameter combinations according to a plurality of stimulation parameters;

[0041] The parameter wireless output unit 34 is used to output multiple stimulation point combinations and multiple stimulation parameter combinations to the implantable spinal cord stimulation module.

[0042] The stimulation point parameter setting unit 32 and the stimulation parameter setting unit 33 are both software interfaces, and the parameter wireless output unit 34 is wireless transmission hardware.

[0043] During two polling cycles (one cycle for each site and parameter), the program-controlled module 3 sets multiple stimulation point combinations and multiple stimulation parameter combinations based on the received stimulation points and stimulation parameters, and outputs them to the implantable spinal cord stimulation module 3. When the two polling cycles are completed, the second signal output unit 24 sends the optimal stimulation point combination and the optimal stimulation parameter combination to the first input unit 31 of the program-controlled module 3, and then the parameter wireless output unit 34 controls the implantable spinal cord stimulation module 4 to automatically perform continuous rehabilitation treatment.

[0044] The stimulation point parameter setting unit 32 and the stimulation parameter setting unit 33 in the program control module 3 set the plurality of stimulation points and the plurality of stimulation parameters received by the first signal input unit 31 into a plurality of stimulation point combinations and stimulation parameter combinations. The stimulation point combination refers to the selection of stimulation electrodes at different positions on the spinal cord so that the target nerve area is stimulated. The stimulation parameter combination involves parameters such as the intensity, frequency, and pulse width of the stimulation signal. Different combinations of these parameters can produce different stimulation effects. The plurality of stimulation point combinations and the plurality of stimulation parameter combinations are output to the implantable spinal cord stimulation module through the parameter wireless output unit 34 to achieve different stimulation treatments for the patient.

[0045] In a preferred embodiment, as shown in FIG3 , the implantable spinal cord stimulation module 4 includes an implantable spinal cord stimulator 41 , a spinal cord stimulation electrode 42 and a spinal cord electrode wire 43 ; the implantable spinal cord stimulation module can also be an integral implantable spinal cord stimulation product that integrates the functions of an implantable spinal cord stimulator, a spinal cord stimulation electrode and a spinal cord electrode wire.

[0046] The implantable spinal cord stimulator 41 is used to receive multiple stimulation point combinations and multiple stimulation parameter combinations, and control the spinal cord stimulation electrode 42 through the spinal cord electrode wire 43 to output stimulation signals in sequence according to the multiple stimulation point combinations and multiple stimulation parameter combinations.

[0047] The implantable spinal cord stimulator 41 controls the spinal cord stimulation electrode 42 using the spinal cord electrode wire 43 and sequentially outputs stimulation signals according to a plurality of pre-set stimulation point combinations and stimulation parameter combinations.

[0048] The stimulation parameters of the implantable spinal cord stimulator 41 generally include voltage or current (stimulation amplitude), frequency of the output stimulation signal, and pulse width (pulse width) of the stimulation signal. The values ​​of the stimulation parameters can be set based on experience. In this step, the values ​​of the preset stimulation parameters are unique and unchanged. For example, the preset stimulation parameters are voltage 2.5V, frequency 70Hz, and pulse width 120μs.

[0049] The spinal cord stimulation electrode 42 has multiple output electrode contacts (points), the specific number being 16 (more or less). A stimulation point combination refers to one or more of all the contacts. For example, the stimulation contacts are numbered #1 to #16, where contact #1 and contact #2 can be used as a stimulation point combination; contact #1, contact #2, and contact #4 can be used as another stimulation point combination. The above combination is only an example to illustrate the meaning of the contact combination. In actual applications, different point combinations can be composed of contacts with some of the same number, all different numbers, different numbers, or the same number or number but different sequence or polarity. Because the various electrode contacts implanted in the human body act on different parts of the human body / nerve, when different points or combinations output stimulation signals, the stimulation effects produced may be different.

[0050] Stimulation signals are output to the patient through these stimulation points with corresponding stimulation parameters. These stimulation signals can directly act on the spinal nerve fibers. The spinal cord stimulation electrode 42 uses different stimulation point combinations in turn to output stimulation signals (the contacts that do not belong to the combination are in a closed state and do not output stimulation signals). Under each stimulation point combination setting, the duration of the output stimulation signal is the same, for example, 15 minutes; on the other hand, the implantable spinal cord stimulator 41 can also use the spinal cord electrode wire 43 to control the spinal cord stimulation electrode 42 to output stimulation signals in turn according to the calculated optimal stimulation points and optimal stimulation parameters. The stimulation is transmitted to the cerebral cortex through the ascending reticular activating system, increasing the local glucose metabolism rate and cerebral blood flow of the brain, promoting the release of excitatory neurotransmitters, and enhancing conscious impulses and brain electrical activity, thereby promoting patient awakening.

[0051] As shown in FIG2 , in a preferred embodiment, the acquisition module 1 includes an EEG acquisition unit 11 , an EMG acquisition unit 12 , and a first signal output unit 13 ;

[0052] The EEG acquisition unit 11 is used to collect EEG signals before and during the stimulation signal on the patient with impaired consciousness through an EEG acquisition cap;

[0053] The myoelectric acquisition unit 12 is used to collect myoelectric signals before and during the stimulation signal on the patient with impaired consciousness through body surface electrodes;

[0054] The first signal output unit 13 is used to output the EEG signal to the processing module via electrode wires or wireless transmission, and to output the EMG signal to the processing module wirelessly.

[0055] The EEG collection cap includes an inner-cap electrode and a cap support structure. The inner-cap electrode is used to collect EEG signals. The cap support structure is used to support the EEG collection cap, providing stable and comfortable support, which helps ensure that the inner-cap electrode can accurately fit the scalp, thereby ensuring the quality and accuracy of the EEG signal.

[0056] The EEG signals and EMG signals of the patient with impaired consciousness collected by the EEG acquisition unit 11 and the EMG acquisition unit 12 before the stimulation signal acts on them can be output to the processing module and converted into human body indicators, and compared with the human body indicators converted from the EEG signals and EMG signals of the patient with impaired consciousness when the stimulation signal acts on them.

[0057] The wireless transmission method adopted by the first signal output unit 13 may be Bluetooth or WIFI.

[0058] The EEG stimulation unit 11 and the EMG acquisition unit 12 in the acquisition module 1 acquire EEG signals and EMG signals when the stimulation signal acts on the patient with impaired consciousness through the EEG acquisition cap and the surface electrodes. The number of EMG acquisition points of the surface electrodes can be 1 to 32. For example, it is feasible to arrange several EMG acquisition electrodes on each of the four limbs, or to arrange only one EMG acquisition electrode on one arm or leg. This realizes the acquisition of the corresponding EEG signals and EMG signals of the patient acted on by a plurality of pre-set stimulation point combinations and stimulation parameter combinations, so as to analyze and calculate the optimal stimulation point combination and the optimal stimulation parameter combination acting on the patient.

[0059] The processing module 2 includes a second signal input unit 21, an algorithm judgment unit 22, a storage and display unit and a second signal output unit 24;

[0060] A second signal input unit 21 is used to receive EEG signals and EMG signals;

[0061] an algorithm judgment unit 22 for converting EEG signals and EMG signals into human body indicators, and determining an optimal stimulation point combination and an optimal stimulation parameter combination from a plurality of stimulation point combinations and a plurality of stimulation parameter combinations according to the human body indicators;

[0062] A storage and display unit, configured to store and display the EEG signal and the EMG signal, human body indicators converted by the algorithm, and an optimal stimulation point combination and an optimal stimulation parameter combination;

[0063] The second signal output unit 24 is used to output the optimal stimulation point combination and the optimal stimulation parameter combination to the program control module 3 .

[0064] The algorithm processing and comparison unit in the processing module 2 processes and analyzes the EEG and EMG signals received by the second signal input unit 21 through the algorithm judgment unit 22 through a pre-stored built-in algorithm, extracts the key information of the EEG and EMG to obtain the optimal stimulation point combination and the optimal stimulation parameter combination, and then stores and displays the EEG signals, EMG signals, human body indicators converted by the algorithm, and the optimal stimulation point combination and the optimal stimulation parameter combination through the storage and display unit. Finally, the second signal output unit 24 outputs the optimal stimulation point combination and the optimal stimulation parameter combination directly to the program control module 3 in a wired manner, so as to automatically set the stimulator according to the optimal stimulation point combination and the optimal stimulation parameters, and perform subsequent continuous stimulation treatment on the patient.

[0065] In a preferred embodiment, the storage and display unit includes a display 231 and a memory 232. The memory 232 is used to store the collected EEG signals, EMG signals, converted human body indicators, and the optimal stimulation point combination and the optimal stimulation parameter combination. The display 231 displays the collected EEG signals, EMG signals, converted human body indicators, comparison process data, and the optimal stimulation point combination and the optimal stimulation parameter combination after comparison to the user.

[0066] The software displays the collected EEG signals, EMG signals, converted human body indicators, comparison process data and the optimal stimulation point combination and optimal stimulation parameter combination to the user (doctor) on the display screen. The doctor can refer to the display results on the display screen and manually set the optimal plan for the patient with consciousness disorder through the stimulation parameter setting unit 33 and the stimulation point parameter setting unit 32 for continuous stimulation treatment.

[0067] In a preferred embodiment, the human body indicators include brain activity indicators and body activity indicators, wherein the brain activity indicators include at least one indicator of the average amplitude, rhythm, ordered entropy, permutation entropy, information interaction connectivity information, and brain interval change recursive information calculated based on the EEG signal; the body activity indicators include the motion monitoring amplitude calculated based on the electromyography signal.

[0068] For example, for multiple stimulation point combinations 1 through n, brain activity index 1 and body activity index 1 can be calculated based on EEG signal 1 and EMG signal 1 during the stimulation signal output from combination 1. And brain activity index n and body activity index n can be calculated based on EEG signal n and EMG signal n during the stimulation signal output from combination n. For ease of description, these are referred to as the human body indexes corresponding to the stimulation point combinations.

[0069] When multiple of the above-mentioned human body indicators are used, corresponding priorities or weights can be preset to focus on the optimization effects of different types of indicators. For example, they can be compared one by one according to the weights. For example, the optimization amounts of various indicators can be weighted statistically with the corresponding weights to calculate the numerical value as the overall optimization effect.

[0070] The goal of this system is to determine the optimal stimulation points and optimal stimulation parameters of the implantable spinal cord stimulation module (implantable spinal cord stimulator). First, the system is initialized. The program control module uses the experience parameters (i.e., several stimulation points and several stimulation parameters) as the initialization parameters according to the settings input by the medical staff to set the point stimulation points and point stimulation parameters of the implantable spinal cord stimulator. For example, the two central electrodes are applied with an electrical stimulation pulse of 2.5V, 70Hz frequency, and 120μs width for 15 minutes. After the patient is stimulated, the acquisition module collects the EEG signal and the EMG signal. After the stimulation of the electrode combination is completed, the electrode combination (stimulation point combination and stimulation parameter combination) is replaced. Stimulation parameter combination), such as changing to two edge electrodes, applying electrical stimulation pulses with a voltage of 2.5V, a frequency of 70Hz, and a wave width of 120μs for 15 minutes, and conducting post-stimulation acquisition module on the patient to collect EEG signals and EMG signals, and continue to change the electrode combination and collect information until the electrode combination polling is completed. The processing module obtains human index results such as the average amplitude, rhythm, ordered entropy, information interaction connectivity information and recursive information of brain interval changes of EEG, as well as human index results of myoelectric movement monitoring amplitude through data processing algorithm, and selects the optimal electrode point combination by comparing the human indexes of each motor combination to determine the electrode point with the best stimulation effect.

[0071] To further determine the electrical stimulation parameters, the amplitude, frequency and pulse width parameters of the electrical stimulation are scanned through fixed electrode points. Each parameter combination is stimulated for 15 minutes, and the EEG and EMG information under different parameter combinations will be obtained. The processing module obtains human index results such as the average amplitude, rhythm, ordered entropy, information interaction connectivity information and recursive information of brain interval changes of the EEG, as well as the human index results of the myoelectric movement monitoring amplitude through the data processing algorithm, selects the optimal electrical stimulation parameters, and determines the electrical stimulation parameters with the best stimulation effect.

[0072] By combining the optimal stimulation points and the optimal stimulation parameters, the best plan for the patient with impaired consciousness can be determined, and subsequent contact stimulation treatment can be carried out. The various stimulation point combinations and stimulation parameter combinations used in this method and their corresponding human indicators can be presented to the user (doctor), and the results under the optimal combination determined by this method can be marked, so that the user (doctor) can read all the results as a whole and choose the appropriate stimulation combination by himself.

[0073] With reference to Figure 4, the operation process of each module in the consciousness disorder awakening system is described in detail:

[0074] The acquisition module 1 starts to collect the EEG signals and EMG signals without outputting stimulation signals to the patient with impaired consciousness.

[0075] The program control module 3 inputs a plurality of stimulation points and a plurality of stimulation parameters through the first signal input unit 31, sets a plurality of stimulation point combinations through the stimulation point parameter setting unit 32, and sets a plurality of stimulation parameter combinations through the stimulation parameter setting unit 33, and then transmits the set plurality of stimulation point combinations and a plurality of stimulation parameter combinations to the implantable spinal cord stimulation module 4 through the parameter wireless output unit 34. The implantable spinal cord stimulator 41 in the implantable spinal cord stimulation module 4 receives the plurality of stimulation point combinations and a plurality of stimulation parameter combinations, and then transmits the plurality of stimulation point combinations and a plurality of stimulation parameter combinations to the spinal cord stimulation electrode 42 through the spinal cord electrode wire 43, and outputs stimulation signals to the patient's body in sequence. When the implantable spinal cord stimulation module 4 outputs stimulation signals (treatment) to the patient, the EEG acquisition unit 11 in the acquisition module 1 acquires the EEG signals through the EEG acquisition unit 11. The cap collects EEG signals when the stimulation signal acts on the patient with impaired consciousness. At the same time, the electromyography acquisition unit 12 collects electromyography signals when the stimulation signal acts on the patient with impaired consciousness through body surface electrodes. Then the first signal output unit 13 outputs the EEG signals and electromyography signals to the processing module 2 through electrode wires or wireless (Bluetooth, WIFI, etc.). The second signal input unit 21 in the processing module 2 receives the EEG signals and electromyography signals. The algorithm judgment unit converts the EEG signals and electromyography signals to obtain human body indicators, and compares and determines the optimal stimulation point combination and the optimal stimulation parameter combination from multiple stimulation point combinations and multiple stimulation parameter combinations based on the human body indicators. During the process, the storage and display unit 22 stores and displays the EEG signals and electromyography signals, human body indicators, comparison process data and comparison result data (optimal stimulation point combination and optimal stimulation parameter combination), etc.

[0076] After the storage and display unit displays multiple optimal stimulation parameter combinations and multiple optimal stimulation parameter combinations through the display screen, the user (doctor) can select according to the displayed multiple optimal stimulation parameter combinations and multiple optimal stimulation parameter combinations. At this time, the second signal output unit 24 and the first signal input unit 31 are closed, and the stimulation point parameter setting unit 32 and the stimulation parameter setting unit 33 are manually input and set by the user (doctor). Then, the optimal stimulation point combination and the optimal stimulation parameter combination selected by the user (doctor) are output to the implantable spinal cord stimulation module 4 through the parameter wireless output unit. Finally, the implantable spinal cord stimulation module 4 performs continuous rehabilitation treatment on patients with consciousness disorders.

[0077] The second signal output unit 24 can also output a unique optimal stimulation point combination and optimal stimulation parameter combination directly to the first input unit 31 of the program control module 3, and then the parameter wireless output unit 34 controls the implantable spinal cord stimulation module 4 to automatically perform continuous rehabilitation treatment.

[0078] This system forms a closed-loop system through the cooperation of external EEG and EMG sampling equipment and spinal cord electrical stimulation equipment implanted in the human body. Through the real-time EEG and EMG information collection and calculation in the closed-loop system, the optimal combination of electrical stimulation electrode points and electrical stimulation parameters are obtained, thereby improving the efficiency of awakening.

[0079] As shown in FIG5 , an embodiment of the present application provides a method for determining a wake-up electrical stimulation scheme for rehabilitation of impaired consciousness. The method can be executed by the processing module in the above system, and includes the following operations:

[0080] S1, when the implantable spinal cord stimulator adopts preset stimulation parameters and outputs stimulation signals in sequence through multiple stimulation point combinations, the human body's electroencephalogram (EEG) signals and electromyographic (EMG) signals are collected.

[0081] The stimulation parameters of an implantable spinal cord stimulator usually include voltage or current (stimulation amplitude), frequency of the output stimulation signal, and pulse width (pulse width) of the stimulation signal. The values ​​of the stimulation parameters can be set based on experience. In this step, the values ​​of the preset stimulation parameters are unique and unchanged. For example, the preset stimulation parameters are voltage 2.5V, frequency 70Hz, and pulse width 120μs.

[0082] The implantable spinal cord stimulator has multiple output electrode contacts (points), and the specific number is, for example, 16 (more or less). In this solution, the stimulation point combination refers to one or more of all the contacts, for example, the stimulation contacts are numbered #1 to #16, where contact #1 and contact #2 can be used as a stimulation point combination; contact #1, contact #2 and contact #4 can be used as another stimulation point combination. The above combination is just an example to illustrate the meaning of the contact combination. In actual applications, different point combinations can be composed of contacts with some of the same numbers, all different numbers, different numbers, the same number or number but different sequence or polarity. Because the various electrode contacts implanted in the human body act on different parts of the human body / nerves, when different points or combinations output stimulation signals, the stimulation effects produced may be different.

[0083] Under fixed stimulation parameters, the stimulator sequentially outputs stimulation signals using different stimulation point combinations (contacts not in the combination are closed and do not output stimulation signals). Under each stimulation point combination setting, the duration of the output stimulation signal is the same, for example, 15 minutes. This step acquires the EEG and EMG signals corresponding to these stimulation processes.

[0084] For example, if multiple stimulation points are combined into combination 1 to combination n, the EEG signal 1 and EMG signal 1 in the process of combination 1 outputting the stimulation signal... the EEG signal n and EMG signal n in the process of combination n outputting the stimulation signal can be collected, that is, each stimulation point combination corresponds to a continuous period of EEG signals and EMG signals.

[0085] Multiple stimulation point combinations can be possible effective point combinations set according to the patient's actual situation and medical experience, rather than all combinations, to avoid using points that are unlikely to produce the expected effect to perform the stimulation process, thereby improving the efficiency of this program.

[0086] There are many options for the location, method, and equipment for collecting EEG and EMG signals, and this solution does not limit them. In some embodiments, EEG signals are EEG signals of multiple brain regions collected by an EEG cap with multiple collection points. Myoelectric signals are myoelectric signals collected by at least one surface electrode arranged on the surface of the skin of the human limbs. The number of myoelectric collection points can be 1 to 32. For example, it is feasible to arrange several myoelectric collection electrodes on each of the limbs, or to arrange only one myoelectric collection electrode on one arm or leg.

[0087] S2. Calculate human body indicators based on the EEG signals and EMG signals corresponding to each stimulation point combination. The human body indicators calculated by this solution can reflect the human body's response to the output process of the stimulation signal, and can specifically include brain activity indicators and body activity indicators. More specifically, the brain activity indicators include at least one of the following indicators: average amplitude, rhythm, ordered entropy, permutation entropy, information interaction connectivity information, and recursive information of brain interval changes calculated based on the EEG signals; the body activity indicators include the movement monitoring amplitude calculated based on the EMG signals.

[0088] For example, for multiple stimulation point combinations 1 through n, brain activity index 1 and body activity index 1 can be calculated based on EEG signal 1 and EMG signal 1 during the stimulation signal output from combination 1. And brain activity index n and body activity index n can be calculated based on EEG signal n and EMG signal n during the stimulation signal output from combination n. For ease of description, these are referred to as the human body indexes corresponding to the stimulation point combinations.

[0089] S3, determining the optimal stimulation point combination from multiple stimulation point combinations based on human body indicators. Under the condition of fixed stimulation parameters, the values ​​or states of human body indicators are usually different under the action of stimulation signals output by different stimulation point combinations. This step can be to screen out one or more stimulation point combinations corresponding to the best human body indicators from all stimulation point combinations, or it can be to screen out one or more stimulation point combinations that achieve the expected stimulation effect. There are multiple optional determination logics, which are specifically introduced in subsequent embodiments.

[0090] A stimulation point combination i is determined through steps S1-S3. When all combinations use the same stimulation parameters to output stimulation signals respectively, the point combination i can bring the most positive awakening effect to the patient.

[0091] S4, in the process of the implantable spinal cord stimulator outputting stimulation signals through the optimal stimulation point combination and sequentially using multiple stimulation parameter combinations, the human body's EEG signals and EMG signals are collected. A stimulation parameter combination refers to a combination of different values, such as the stimulation signal amplitude, stimulation signal frequency, and stimulation signal pulse width. The stimulation parameters have corresponding settable ranges, such as the stimulation amplitude of 0 to 10V, etc. When there is only one adjustable stimulation parameter, different values ​​can also be understood as a stimulation parameter combination. For example, in some embodiments, only the stimulation frequency parameter can be changed. Parameter combination 1 is voltage 2.5V, frequency 70Hz, and wave width 120μs; parameter combination 2 is voltage 2.5V, frequency 140Hz, and wave width 120μs. In essence, the only difference between the two parameter combinations is the frequency of the stimulation signal.

[0092] When there are multiple adjustable stimulation parameters, the number of possible stimulation parameter combinations is greater than the number of the above-mentioned stimulation point combinations. Therefore, it is more necessary to pre-set possible effective stimulation parameter combinations based on the patient's actual situation and medical experience, rather than all combinations, to avoid using stimulation parameters that are unlikely to produce the expected effect to perform the stimulation process, so as to improve the efficiency of this program.

[0093] In the case of a fixed stimulation point combination (i.e., the optimal stimulation point combination), the stimulator sequentially outputs stimulation signals using different stimulation parameter combinations (contacts not in the combination are closed), with each stimulation parameter combination outputting stimulation signals for the same duration, for example, 15 minutes. This step acquires the EEG and EMG signals corresponding to these stimulation processes.

[0094] For example, if multiple stimulation parameters are combined into parameter 1 to parameter n, the EEG signal 1 and the EMG signal 1 in the process of outputting the stimulation signal using parameter 1 can be collected... The EEG signal n and the EMG signal n in the process of outputting the stimulation signal using parameter n can be collected.

[0095] S5, calculating the human body index based on the EEG signal and the EMG signal corresponding to each stimulation parameter combination. For details, refer to step S2, and the same index and calculation method as in this step can be used.

[0096] S6. Determine the optimal stimulation parameter combination from multiple stimulation parameter combinations based on the human body indicators. In the case of a fixed stimulation point combination, the values ​​or states of the human body indicators are usually different under the action of different stimulation parameter combinations. This step can be to screen out one or more stimulation parameter combinations corresponding to the relatively optimal human body indicators from all stimulation parameter combinations, or it can be to screen out one or more stimulation parameter combinations that achieve the expected stimulation effect. There are multiple optional determination logics, which are specifically introduced in subsequent embodiments.

[0097] Through steps S4-S6, a stimulation parameter combination j is determined. When using the optimal stimulation point combination and outputting stimulation signals using different parameter combinations, parameter combination j can achieve the most positive awakening effect on the patient. This protocol has now determined the stimulation point combination i and stimulation parameter combination j. Physicians can use this result to determine the optimal protocol for continuous stimulation therapy for patients with impaired consciousness.

[0098] Specifically, the various stimulation point combinations and stimulation parameter combinations used in this method and their corresponding human body indicators can be presented to the user (doctor), and the results under the optimal combination determined by this method can be identified, so that the user (doctor) can read all the results as a whole and choose the appropriate stimulation combination by himself.

[0099] As shown in FIG6 , in one embodiment, step S3 includes the following operations:

[0100] S31A, respectively calculating the optimization effects of various human body indicators corresponding to multiple stimulation point combinations compared to the human body indicators before the start of stimulation. Regarding the human body indicators before the start of stimulation, it can be that before outputting the stimulation signal, the EEG signals and EMG signals are first collected for a period of time (for example, 15 minutes, the same as the duration of the stimulation signal output by each combination), and then the corresponding human body indicators are calculated; or the human body indicators before that can be obtained, such as those collected and calculated when the patient was last diagnosed.

[0101] S32A: Compare the optimization effects corresponding to multiple stimulation point combinations, and determine the stimulation point combination with the best optimization effect as the optimal stimulation point combination. In this embodiment, the optimization effects corresponding to all point combinations are compared with each other, and the point combination with the best optimization effect is selected.

[0102] If average amplitude is used as one of the indicators, assuming the optimization effect of combination 1 is B1-C1 mV, B1>C1, and the optimization effect of combination 2 is 0 mV, then combination 1 is the combination with relatively better optimization effect. By comparing all combinations in this way, the point combination with the best optimization effect can be determined.

[0103] Step S6 includes the following operations:

[0104] S61A calculates the optimization effects of various human motion indices corresponding to multiple stimulation parameter combinations, compared to the human motion indices before the stimulation began. For details, refer to S31A, and the calculation method used is the same. This step calculates the optimization effects corresponding to parameter 1...parameter n.

[0105] S62A, comparing the optimization effects corresponding to the multiple stimulation parameter combinations, and determining the stimulation parameter combination with the best optimization effect as the optimal stimulation parameter combination. For details, see S32A. In this embodiment, the optimization effects corresponding to all parameter combinations are compared, and the parameter combination with the best optimization effect is selected. By comparing all parameter combinations in this manner, the parameter combination with the best optimization effect can be determined.

[0106] Regarding the above-mentioned human body indicators and corresponding optimization effects, further including:

[0107] Average amplitude: The optimization effect refers to the increase in the average amplitude during the stimulation process, that is, the difference between the average amplitude during the stimulation process and the average amplitude before the stimulation begins. The larger the difference, the better the optimization effect.

[0108] Rhythm, its optimization effect means that the continuity of amplitude is improved, it appears intermittent before the start of stimulation and appears continuous during the stimulation process.

[0109] Ordered entropy, its optimization effect refers to the increase in the ordered entropy value of each monitoring area during the stimulation process compared with the ordered entropy value before stimulation. The greater the increase, the better the optimization effect.

[0110] Permutation entropy, its optimization effect refers to the increase in the permutation entropy value of each monitoring area during the stimulation process compared to the permutation entropy value before stimulation. The greater the increase, the better the optimization effect.

[0111] The optimization effect of information interaction connectivity refers to the significant increase in the number of active channels during the stimulation process compared to before the stimulation, as well as the increase in activity. The greater the increase in the number of active channels and the higher the increase in activity, the better the optimization effect.

[0112] The optimization effect of the recursive information of brain interval change refers to the reduction in the brain interval change index value during the stimulation process compared to the brain interval change index value before the stimulation. The greater the reduction, the better the optimization effect.

[0113] The optimization effect of the active motion monitoring amplitude refers to the increase in the active motion monitoring amplitude during the stimulation process, that is, the difference between the active motion monitoring amplitude during the stimulation process and the active motion monitoring amplitude before the stimulation begins (the active motion monitoring amplitude of patients with impaired consciousness is 0). The larger the difference, the better the optimization effect.

[0114] Based on the optimization effect of each indicator, the overall optimization effect of all indicators can also be calculated comprehensively.

[0115] In steps S3 and S6, when multiple of the aforementioned human body indicators are used, corresponding priorities and / or weights may be preset to prioritize the optimization effects of different types of indicators. For example, the optimization effects of the various human body indicators may be compared item by item based on their priorities. For example, the optimization amounts of the various indicators may be weighted and statistically added to the corresponding weights to calculate a numerical value as the overall optimization effect. Alternatively, both of the above methods may be employed simultaneously, comparing the optimization effects of the various human body indicators item by item while calculating and comparing the overall optimization effect. The optimal position combination and optimal parameter combination may be determined based on the comparison results.

[0116] In some embodiments, in addition to the four human body indicators of average amplitude, permutation entropy, motion monitoring amplitude, and information interaction connectivity information, the aforementioned additional brain indicators are also used. In these embodiments, in the optimization effect comparison operation in steps S31A-S32A and S61A-S62A, if a comparison is performed item by item, the four indicators of average amplitude, permutation entropy, motion monitoring amplitude, and information interaction connectivity information are prioritized, so that the optimal bit combination i and the optimal parameter combination j have the highest relative improvement in average amplitude, permutation entropy, active motion monitoring amplitude, information interaction connectivity information, and increased number of active channels. If the overall optimization effect is calculated, higher weights can be assigned to these four indicators so that the calculation result is more influenced by the improvement in these four indicators.

[0117] In actual application, the comparison results can be presented to the user, and the optimal combination can be arranged in front according to the degree of optimization effect, and all stimulation combinations can be given in an overall order, or only the optimal group or the first few groups can be presented for reference and selection by the user (doctor).

[0118] As shown in FIG7 , in one embodiment, step S3 includes the following operations:

[0119] S31B, respectively calculating the optimization effects of the human body indicators corresponding to the multiple stimulation point combinations compared to the human body indicators before the stimulation begins.

[0120] S32B compares the optimization effect with the expected effect, and determines the stimulation point combination with an optimization effect that exceeds the expected effect as the optimal stimulation point combination. Unlike the previous embodiment, this embodiment predetermines the eligibility criteria for the optimization effect of various human body indicators. This step determines whether the human body indicators and optimization effects corresponding to each point combination meet the eligibility criteria, thereby determining the optimal stimulation point combination.

[0121] Step S6 includes the following operations:

[0122] S61B, respectively calculating the optimization effects of the human body indicators corresponding to the multiple stimulation parameter combinations compared to the human body indicators before the stimulation begins;

[0123] S62B, comparing the optimized effect with the expected effect, and determining the stimulation parameter combination with an optimized effect higher than the expected effect as the optimal stimulation parameter combination.

[0124] As an example, the expected effects (qualification conditions) of the optimization effects of various human body indicators may be:

[0125] Average amplitude: After the stimulation starts, the average amplitude can increase from C1 mV to B1 mV, B1 is the preset threshold (qualified condition), the test range is 0~A1 mV, where 0 <C1<B1<A1。

[0126] Rhythm: After the stimulation begins, the amplitude continuity increases and changes from intermittent performance to continuous continuity (qualified condition).

[0127] Ordered entropy: After the stimulation begins, the ordered entropy value of each monitoring area can be increased by B2, B2 is the preset threshold (qualified condition), the test range is 0 to A2, where 0 <B2<A2。

[0128] Permutation Entropy: After the stimulation begins, the permutation entropy value of each monitoring area can be increased by B3, B3 is the preset threshold (qualified condition), the test range is 0 to A3, where 0 <B3<A3。

[0129] Information interaction connectivity: After the stimulation begins, the number of active channels can significantly increase by C4 or C4% (qualified condition); the activity of the activated channels can change from 0 to B4, where B4 is the preset threshold (qualified condition), and the test range is 0 to A4, where 0 <B4<A4。

[0130] Recursive index of brain interval change: After the stimulation begins, the brain interval change index value can be reduced from B5 to C5, C5 is the preset threshold (qualified condition), the test range is 0 to A5, where 0 <C5<B5<A5。

[0131] Active action monitoring: after the stimulation starts, the action monitoring amplitude can change from a stable state of 0 to a fluctuating state of non-zero value A6 (qualified condition).

[0132] In the operations of comparing the optimization effect with the expected effect in the above steps S32B and S62B, the optimization effects of the average amplitude, permutation entropy, motion monitoring amplitude and information interaction connectivity information are preferentially compared with the corresponding expected effects, and the stimulation point combinations and stimulation parameter combinations that meet the qualified conditions of these four human body indicators are screened out.

[0133] In actual application, the comparison results can be presented to the user. After comparing the optimization effects corresponding to each stimulation combination with the corresponding expected effects, the best group or the top few groups are output for the user (doctor) to refer to and select.

[0134] As shown in FIG8 , in one embodiment, step S3 includes the following operations:

[0135] S31C, respectively calculating the optimization effects of the human body indicators corresponding to the multiple stimulation point combinations compared with the human body indicators before the stimulation begins;

[0136] S32C: Compare the optimized effect with the corresponding expected effect, and select the stimulation point combination with an optimized effect higher than the expected effect. This is similar to step S32B in the previous embodiment, but differs in that this embodiment sets relatively few expected effects (for example, only setting corresponding expected effects for some human body indicators), or relatively low expected effects (relatively lower thresholds), and first selects the point combination (which may be multiple or only one) that achieves the expected effect from all point combinations.

[0137] S33C, comparing the optimization effects corresponding to the screened stimulation point combinations, and determining the stimulation point combination with the best optimization effect among the screened stimulation point combinations as the optimal stimulation point combination.

[0138] Step S6 includes the following operations:

[0139] S61C, respectively calculating the optimization effects of the human body indicators corresponding to the multiple stimulation parameter combinations compared with the human body indicators before the stimulation begins;

[0140] S62C, compare the optimized effect with the expected effect, and select the stimulation parameter combination with the optimized effect higher than the expected effect;

[0141] S63C, comparing the optimization effects corresponding to the screened stimulation parameter combinations, and determining the stimulation parameter combination with the best optimization effect among the screened stimulation parameter combinations as the optimal stimulation parameter combination.

[0142] In the operations of comparing the optimization effects with the expected effects in steps S32C and S62C, the optimization effects of average amplitude, permutation entropy, motion monitoring amplitude, and information interaction connectivity information are preferentially compared with the corresponding expected effects, thereby screening out stimulation point combinations and stimulation parameter combinations that meet the qualified conditions for these four human body indicators. In steps S33C and S63C, the optimization effects of average amplitude, permutation entropy, motion monitoring amplitude, and information interaction connectivity information are preferentially compared. Only when the optimization effects of these four indicators are identical are the optimization effects of other indicators further determined.

[0143] In actual application, the comparison results can be presented to the user. After comparing the optimization effects corresponding to each stimulation combination with the corresponding expected effects and comparing the groups with each other, the best group or the top few groups are output for the user (doctor) to refer to and select.

[0144] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0145] The present application is described with reference to the flow chart and / or block diagram of the method, device (system), and computer program product according to the embodiment of the present application. It should be understood that each flow process and / or box in the flow chart and / or block diagram and the combination of the flow process and / or box in the flow chart and / or block diagram can be realized by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processing machine or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device produce a device for realizing the function specified in one flow chart flow or multiple flows and / or one box or multiple boxes of the block diagram.

[0146] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a product including an instruction device that implements the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0147] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0148] Obviously, the above embodiments are merely examples for clarity of explanation and are not intended to limit the implementation methods. Those skilled in the art will appreciate that other variations or modifications can be made based on the above description. It is not necessary and impossible to enumerate all implementation methods here. Obvious variations or modifications arising therefrom remain within the scope of protection of this application.

Claims

1. A method for determining a wake-up electrical stimulation scheme for rehabilitation of consciousness disorders, characterized in that: include: In the process of the implantable spinal cord stimulator using preset stimulation parameters and outputting stimulation signals respectively through multiple stimulation point combinations in sequence, the brain electrical signals and the myoelectric signals of the human body are collected, wherein the difference between the different stimulation point combinations includes at least one difference in the number of points, the site of action, and the polarity; Calculating human body indicators based on the EEG signals and the EMG signals corresponding to each combination of stimulation points; Determining an optimal stimulation point combination from the plurality of stimulation point combinations according to the human body indicators; In the process of the implantable spinal cord stimulator outputting stimulation signals respectively through the optimal stimulation point combination and sequentially using a plurality of stimulation parameter combinations, the human body's electroencephalogram signals and electromyographic signals are collected, wherein the stimulation parameters include at least one parameter of the stimulation amplitude, the stimulation frequency, and the pulse width, and the difference between different stimulation parameter combinations is that the value of at least one parameter is different; Calculating human body indicators for the EEG signal and the EMG signal corresponding to each stimulation parameter combination; An optimal stimulation parameter combination is determined from the multiple stimulation parameter combinations according to the human body indicators.

2. The method according to claim 1, characterized in that The human body indicators include brain activity indicators and body activity indicators, wherein the brain activity indicators include at least one indicator of average amplitude, rhythm, ordered entropy, permutation entropy, information interaction connectivity information, and brain interval change recursive information calculated based on the electroencephalographic signals; the body activity indicators include motion monitoring amplitude calculated based on the electromyographic signals.

3. The method according to claim 2, characterized in that Determining an optimal stimulation point combination from the plurality of stimulation point combinations according to the human body index comprises: Respectively calculating the optimization effects of the human body indicators corresponding to the multiple stimulation point combinations compared with the human body indicators before the stimulation begins; Comparing the optimization effects corresponding to the multiple stimulation point combinations, and determining the stimulation point combination with the best optimization effect as the optimal stimulation point combination; Determining an optimal stimulation parameter combination from the multiple stimulation parameter combinations according to the human body index includes: Respectively calculating the optimization effects of the human body indicators corresponding to the multiple stimulation parameter combinations compared with the human body indicators before the stimulation begins; Compare the optimization effects corresponding to the multiple stimulation parameter combinations, and select the stimulation with the best optimization effect. The parameter combination is determined as the optimal stimulation parameter combination.

4. The method according to claim 3, characterized in that In the operation of comparing the optimization effects, priority is given to the optimization effects of average amplitude, permutation entropy, action monitoring amplitude and information interaction connectivity information.

5. The method according to claim 2, characterized in that: Determining an optimal stimulation point combination from the plurality of stimulation point combinations according to the human body index comprises: Respectively calculating the optimization effects of the human body indicators corresponding to the multiple stimulation point combinations compared with the human body indicators before the stimulation begins; Comparing the optimization effect with the expected effect, and determining the stimulation point combination with the optimization effect higher than the expected effect as the optimal stimulation point combination; Determining an optimal stimulation parameter combination from the multiple stimulation parameter combinations according to the human body index includes: Respectively calculating the optimization effects of the human body indicators corresponding to the multiple stimulation parameter combinations compared with the human body indicators before the stimulation begins; The optimization effect is compared with the expected effect, and the stimulation parameter combination with the optimization effect higher than the expected effect is determined as the optimal stimulation parameter combination.

6. The method according to claim 2, characterized in that Determining an optimal stimulation point combination from the plurality of stimulation point combinations according to the human body index comprises: Respectively calculating the optimization effects of the human body indicators corresponding to the multiple stimulation point combinations compared with the human body indicators before the stimulation begins; Comparing the optimization effect with the corresponding expected effect, screening out the stimulation point combination whose optimization effect is higher than the expected effect; Comparing the optimization effects corresponding to the screened stimulation point combinations, determining the stimulation point combination with the best optimization effect among the screened stimulation point combinations as the optimal stimulation point combination; Determining an optimal stimulation parameter combination from the multiple stimulation parameter combinations according to the human body index includes: Respectively calculating the optimization effects of the human body indicators corresponding to the multiple stimulation parameter combinations compared with the human body indicators before the stimulation begins; Comparing the optimization effect with the expected effect, and screening out a stimulation parameter combination whose optimization effect is higher than the expected effect; The optimization effects corresponding to the screened stimulation parameter combinations are compared, and the stimulation parameter combination with the best optimization effect among the screened stimulation parameter combinations is determined as the optimal stimulation parameter combination.

7. The method according to claim 5 or 6, characterized in that: In the operation of comparing the optimization effect with the expected effect, the optimization effect of the average amplitude, the permutation entropy, the action monitoring amplitude and the information interaction connectivity information is preferentially compared with the corresponding expected effect.

8. The method according to any one of claims 3 to 6, characterized in that: The optimization effect of the average amplitude includes the increase in the average amplitude; the optimization effect of the rhythm includes the improvement in amplitude continuity, and the change from intermittent performance to continuous continuity; the optimization effect of the ordered entropy includes the increase in the ordered entropy value of each monitoring area; the optimization effect of the permutation entropy includes the increase in the permutation entropy value of each monitoring area; the optimization effect of the information interaction connectivity information includes the increase in the number of active channels and the increase in the activity of active channels; the optimization effect of the recursive information of brain interval changes includes the decrease in the value of the brain interval change index; the optimization effect of the motion monitoring amplitude includes the increase in the motion monitoring amplitude.

9. The method according to claim 1, characterized in that: The EEG signals are EEG signals of multiple brain regions collected by an EEG cap provided with multiple collection points; The counted electromyographic signal is an electromyographic signal collected by at least one surface electrode arranged on the skin surface of the human limbs.

10. A device for determining a wake-up electrical stimulation scheme for rehabilitation of consciousness disorders, characterized in that: include: A processor and a memory connected to the processor; wherein the memory stores instructions executable by the processor, and the instructions are executed by the processor so that the processor executes the method for determining a wake-up electrical stimulation scheme for consciousness disorders as described in any one of claims 1-9.

11. A system for promoting awakening for rehabilitation of impaired consciousness, characterized in that: include: A program control module, used for setting a plurality of stimulation point combinations and a plurality of stimulation parameter combinations, wherein the difference between different stimulation point combinations includes at least one difference in the number of points, the site of action, and the polarity, and the stimulation parameters include at least one parameter of the stimulation amplitude, the stimulation frequency, and the pulse width, and the difference between different stimulation parameter combinations is that the value of at least one parameter is different; An implantable spinal cord stimulation module, configured to sequentially output stimulation signals according to the plurality of stimulation point combinations and the plurality of stimulation parameter combinations; An acquisition module, used for acquiring EEG signals and EMG signals when the stimulation signal acts on a patient with impaired consciousness; A processing module is used to process the EEG signal and the EMG signal to obtain human body indicators, and determine the optimal stimulation point combination and the optimal stimulation parameter combination from the multiple stimulation point combinations and the multiple stimulation parameter combinations according to the human body indicators.

12. The system according to claim 11, characterized in that The program control module includes a first signal input unit, a stimulation point parameter setting unit, a stimulation parameter setting unit and a parameter wireless output unit; The first signal input unit is used to receive a plurality of stimulation points and a plurality of stimulation parameters; The stimulation point parameter setting unit is used to set a plurality of stimulation point combinations according to the plurality of stimulation points; The stimulation parameter setting unit is used to set a plurality of stimulation parameter combinations according to the plurality of stimulation parameters; The parameter wireless output unit is used to output the multiple stimulation point combinations and the multiple stimulation parameter combinations to the implantable spinal cord stimulation module.

13. The system according to claim 11, characterized in that The implantable spinal cord stimulation module includes an implantable spinal cord stimulator, a spinal cord stimulation electrode and a spinal cord electrode wire; The implantable spinal cord stimulator is used to receive the multiple stimulation point combinations and the multiple stimulation parameter combinations, and control the spinal cord stimulation electrodes through the spinal cord electrode wires to output stimulation signals in sequence according to the multiple stimulation point combinations and the multiple stimulation parameter combinations.

14. The system according to claim 11, characterized in that The acquisition module includes an EEG acquisition unit, an EMG acquisition unit and a first signal output unit; The EEG acquisition unit is used to collect EEG signals before the stimulation signal acts on the patient with impaired consciousness and when the stimulation signal acts on the patient with impaired consciousness through an EEG acquisition cap; The electromyographic acquisition unit is used to acquire the electromyographic signals before the stimulation signal acts on the patient with impaired consciousness and when the stimulation signal acts on the patient with impaired consciousness through body surface electrodes; The first signal output unit is used to output the EEG signal and the EMG signal to the processing module via electrode wires or wireless transmission.

15. The system according to claim 11, characterized in that The processing module includes a second signal input unit, an algorithm judgment unit, a storage and display unit, and a second signal output unit; The second signal input unit is used to receive the EEG signal and the EMG signal; The algorithm judgment unit is used to convert the EEG signal and the EMG signal to obtain human body indicators, and compare and determine the optimal stimulation point combination and the optimal stimulation parameter combination from the multiple stimulation point combinations and the multiple stimulation parameter combinations according to the human body indicators; The storage and display unit is used to store and display the EEG signal, the EMG signal, the human body index converted by the algorithm, and the optimal stimulation point combination and the optimal stimulation parameter combination; The second signal output unit is used to output the optimal stimulation point combination and the optimal stimulation parameter combination to the program control module.

16. The system according to claim 11, characterized in that The human body indicators include brain activity indicators and body activity indicators, wherein the brain activity indicators include at least one indicator of average amplitude, rhythm, ordered entropy, permutation entropy, information interaction connectivity information, and brain interval change recursive information calculated based on the electroencephalographic signals; the body activity indicators include motion monitoring amplitude calculated based on the electromyographic signals.

17. The system according to claim 11, characterized in that The processing module is used to obtain the EEG signal and the EMG signal when the implantable spinal cord stimulator adopts preset stimulation parameters and outputs stimulation signals respectively through the multiple stimulation point combinations in sequence, calculate human body indicators for the EEG signal and the EMG signal corresponding to each stimulation point combination, and determine the optimal stimulation point combination from the multiple stimulation point combinations based on the human body indicators.

18. The system according to claim 17, characterized in that The processing module is used to respectively calculate the optimization effects of the human body indicators corresponding to the multiple stimulation point combinations compared with the human body indicators before the stimulation starts, compare the optimization effects corresponding to the multiple stimulation point combinations, and determine the stimulation point combination with the best optimization effect as the optimal stimulation point combination; or compare the optimization effect with the expected effect, and determine the stimulation point combination with the optimization effect higher than the expected effect as the optimal stimulation point combination; or compare the optimization effect with the corresponding expected effect, screen out the stimulation point combination with the optimization effect higher than the expected effect, further compare the optimization effects corresponding to the screened stimulation point combinations, and determine the stimulation point combination with the best optimization effect among the screened stimulation point combinations as the optimal stimulation point combination.

19. The system according to claim 17, characterized in that The processing module is used to obtain the EEG signal and the EMG signal during the process of the implantable spinal cord stimulator outputting stimulation signals through the optimal stimulation point combination and sequentially using multiple stimulation parameter combinations, calculate human body indicators for the EEG signal and the EMG signal corresponding to each stimulation parameter combination, and determine the optimal stimulation parameter combination from the multiple stimulation parameter combinations based on the human body indicators.

20. The system according to claim 19, characterized in that The processing module is used to respectively calculate the optimization effects of the human body indicators corresponding to the multiple stimulation parameter combinations compared with the human body indicators before the stimulation begins; compare the optimization effects corresponding to the multiple stimulation parameter combinations, and determine the stimulation parameter combination with the best optimization effect as the optimal stimulation parameter combination; or compare the optimization effect with the expected effect, and determine the stimulation parameter combination with the optimization effect higher than the expected effect as the optimal stimulation parameter combination; or compare the optimization effect with the expected effect, screen out the stimulation parameter combination with the optimization effect higher than the expected effect, further compare the optimization effects corresponding to the screened stimulation parameter combinations, and determine the stimulation parameter combination with the best optimization effect among the screened stimulation parameter combinations as the optimal stimulation parameter combination.

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